Extraction of morphological features of technical systems from Russian patents using dependency tree analysis

The article presents a methodology for extracting morphological features of technical systems in the form of device components and connections between them. The main section of Russian patents claims is chosen as the subject of the study for data extraction. Information about device components is the most fundamental and important part. It can be used in many tasks of computer-aided patent analysis, while the search for effective approaches to extracting such information is still in progress. In the present inquiry, computer-aided development of inventions is considered as a range of applications for such data. The aim of the study was to explore the quality of data extraction using dependency tree analysis for Russian language. The dependency tree is the result of markup by natural language processing tools. Several parsers were chosen for the comparison: UdPipe, Stanza, DeepPavlov and spaCy. The output data are presented in the form of semantic SAO (Subject-Action-Object) structures. The quality of data extraction has been evaluated using precision, recall and F1 metrics. For this purpose, 20 patent claims with 252 SAO structures were manually marked. Under the current methodological constraints, we were able to extract from the dataset 79 % of the SAO structures at best according to the recall metric with a non-strict data evaluation, i.e. without accounting for the completeness of noun groups. The value of F1-measure is lower and ranges from 48 % to 66 % depending on the evaluation type. Conclusions are drawn about the current level of the syntactic analyzer performance within the field of application under review. The results can be useful for developing efficient approaches to extracting structured data from Russian patent arrays.

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